Degradation assessment of bearing based on machine learning classification matrix

In the broad framework of degradation assessment bearing, final objectives bearing condition monitoring is to evaluate different states and estimate quantitative analysis degree performance degradation. Machine learning classification matrices have been used train models based on health data real time feedback. Diagnostic prognostic driven perspective in prior research work improve assessment. Industry 4.0 has required advanced diagnostic algorithm enhance accuracy models. A model which machine matrix assess proposed model. Review demonstrates comparisons among available state-of-the-art methods. end, unexplored technical challenges niches opportunity for future researchers are discussed.